With the advent of the software-defined radio, many choices now exist for signals which can be used in the transmission of data in a wireless communications system. The reproduction of these signals is often a complex process; one of the most commonly accepted techniques is to store the signals as digitized samples in memory, and then read those samples at some prescribed rate into a digital-to-analog converter. This technique is commonly called Arbitrary Waveform Generation (AWG) and may be used to re-create any signal provided the bandwidth of the signal being produced is less than half the rate at which the samples are read out of memory (this is commonly referred to as the Nyquist criterion for signal reproduction).
In a communications system using AWG-type waveform generation, each individual transmitted data symbol must be represented by a complex (i.e. vector) analog signal which is reproduced from its individual digitized samples stored in memory. In sophisticated communications systems, large arrays of memory are required to store all the samples needed to reproduce all the analog signals which are required for the communications system to function.
The problem is further exacerbated if the communications system uses signals of long duration, since the number of digitized samples (and, correspondingly, the amount of memory needed) increases proportionately with the duration of the signals.
In spread spectrum-type communications systems it is common that the analog signals occupy a bandwidth many times greater than that of the data which is being transmitted. This further increases the memory requirements, since the analog signals must be sampled at rates much higher than the Nyquist rate of the transmitted data. In addition, spread spectrum communications systems often use N-ary forms of signaling, wherein one of N different transmitted analog signals is used to represent each data symbol (for pseudo-noise sequence based systems, this is called Code Shift Keying). This form of modulation is advantageous since it reduces the required symbol rate by a factor of log2 N. Sampled versions of each of the N analog symbols must be stored, further increasing the memory requirements in the transmitter.
This situation is further compounded when the transmitted signals have a duration which is longer than the time period between the start of each of the data symbols. This circumstance may arise when signals with large time-bandwidth products are used, for instance in a chirp-based communications system. If the duration of each of the transmitted analog signals has some time, T, and the time period between the start of each of the data symbols has some shorter time, τ, then at any point there will be T/t=O overlapping signals which must be synthesized by the transmitter. Each of these signals must be produced independently, usually by O independent synthesizer paths having their own memory, associated addressing, control circuitry, and digital-to-analog conversion. This typical configuration is shown in the Prior Art block diagram of FIG. 7. To generate the complete transmitted signal, all of the O signals must be summed together at the output of their respective digital-to-analog converters.
Thus a major concern in a communications system which uses sampled signals to represent transmitted data is one of hardware complexity. Specifically, there are two factors which dominate: first, for a system which uses a spread-spectrum form of modulation, the sample rate of the transmitted signal must be many times higher than the sample rate of the data to be transmitted. This means that the hardware must function at much higher clock rates than is required by the symbol rate of the data. From a power consumption and complexity perspective, it is always preferable to minimize the circuitry which operates at the system's highest clock speeds. Second, if the system is transmitting overlapping signals, an independent signal path must be provided for each of the O overlapping signals (as shown in Prior Art FIG. 7), thus increasing the amount signal generating circuitry by the same amount.
It is possible to reduce the number of D/A converters to a single device by summing the digital samples as they are clocked out of memory, before passing them to the D/A converter. In order to do this, an O-input binary adder must be inserted before the D/A converter and the number of bits of resolution of the D/A converter must be increased. Since this part of the transmitter's circuitry operates at the system's highest clock speeds, doing this will increase the power requirements of the transmitter significantly. All in all, the extra circuitry required does not gamer much of an advantage over using O separate D/A converters.
In a communications system which uses large time-bandwidth product signals to represent data symbols (for instance, chirp signals in Chirp Spread Spectrum systems), not being able to overlap the transmitted signals creates severe performance constraints. This is because the time-bandwidth product of a chirp signal represents a figure of merit comparable to processing gain in other types of spread spectrum system, and it behooves the communications designer to use signals with as large a time-bandwidth product as possible to take advantage of the benefits processing gain provides.
On the other hand, any large time-bandwidth product signal (be it a chirp signal or whatever) will, by definition, be long in duration. If signals in a communications system are not allowed to overlap, then the transmitter must wait for the current signal to end before starting transmission of the next signal. This means that, in such a circumstance, the duration of the data symbols is set by the duration of the transmitted signal. As mentioned above, this duration is typically quite long for signals with a large time-bandwidth products. A long duration between data symbols means lower data throughputs. If more data throughput is needed, the time-bandwidth product of the transmitted signals must be reduced, which reduces processing gain. Thus there is a natural tradeoff between processing gain (i.e. time-bandwidth product) and data rate (i.e. the duration of the data symbols) in non-overlapping systems.
Many signals with large time-bandwidth products (including chirp signals) have a property called Time Shift Orthogonality which ensures similar signals are orthogonal to each other provided they observe a minimum spacing of their start times. The required minimum spacing is related to the signal's occupied bandwidth, and is generally very small in relation to the duration of the signal. If time-shift orthogonality is taken advantage of, and large time-bandwidth product signals are allowed to overlap, then the data rate and the processing gain of the transmitter may be chosen independently.
U.S. Pat. No. 5,204,877 ('877 patent), published Apr. 20, 1993 and titled “Spread Spectrum modulating device” describes a hardware structure for producing PN sequences from a waveform memory with a counter and shift register; however, it can generate only multiple “spread spectrum codes” (PN sequences) and uses only either Code Shift Keying (CSK) or On-Off Keying (OOK) as a modulation method. The '877 patent cannot use arbitrary waveforms nor use any type of modulation. Also, the length M, of the counter is equal to the spread spectrum code (i.e. the signal) length, which may be detrimentally long. The '877 patent is also a “data multiplexer”, turning a serial stream of data into parallel signal streams, which may be disadvantageous.
This device and method provide a solution to the pitfalls of increased complexity and power consumption when using a transmitter which transmits data with overlapping signals with large time-bandwidth products. Overlapping the signals allows the symbol rate and the processing gain in such systems to be chosen independently, thus improving their performance.